Measurement Invariance of Early Development Instrument across age groups

Mousavi, Afrooz; Krishnan, V.

doi:10.1037/e500122015-055

Cited by 3 publications

(6 citation statements)

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“…In recent years, DIF has been widely used to ensure the internal validity of psychological, educational, and medical quality of life test scores across different demographic variables such as gender (e.g., Zampetakis et al, 2017), ethnic background (e.g., Jones et al, 2016), age groups (e.g., Estabrook et al, 2015), and socioeconomic status (e.g., Thielemann et al, 2018). DIF assesses whether the probability of responding to a specific item is different for different groups after controlling the ability [10,11]. There are two forms of DIF known as uniform and nonuniform.…”

Section: Differential Item Functioning (Dif)mentioning

confidence: 99%

“…Analyses indicated that the Persian version of the OHI Scale has reliability as a measure of well-being and provided some preliminary evidence of construct validity [7] A brief review of these previous studies on OHI shows the lack of evaluation of OHI fairness/equivalence in measuring happiness among identified groups. Measurement equivalence, also known as differential item functioning (DIF), is an important part of the process of validating questionnaires to test whether the probability of responding to a specific item exhibits different statistical properties for different identifiable groups after controlling the construct being measured [10,11]. Therefore, the goal of this study was to assess measurement equivalence of happiness by means of OHI across gender and marital status.…”

Section: Introductionmentioning

confidence: 99%

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Measurement Invariance and Psychometric Analysis of Oxford Happiness Inventory Scale across Gender and Marital Status

Mousavi

Sharafi

Mahmoudi

et al. 2020

BioMed Research International

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Background. The Oxford Happiness Inventory (OHI) is a self-report tool to measure happiness. A brief review of previous studies on OHI showed the lack of evaluation of OHI fairness/equivalence in measuring happiness among identified groups. Methods. To examine the psychometric properties and measurement invariance of the OHI, responses of 500 university students were analyzed using item response theory and ordinal logistic regression (OLR). Relevant measures of effect size were utilized to interpret the results. Differential test functioning was also evaluated to determine whether there is an overall bias at the test level. Results. OLR analysis detected four items across gender and two items across marital status to function differentially. An assessment of effect sizes implied negligible differences for practical considerations. Conclusions. This study was a significant step towards providing theoretical and practical information regarding the assessment of happiness by presenting adequate evidence regarding the psychometric properties of OHI.

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Section: Differential Item Functioning (Dif)mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Measurement Invariance and Psychometric Analysis of Oxford Happiness Inventory Scale across Gender and Marital Status

Mousavi

Sharafi

Mahmoudi

et al. 2020

BioMed Research International

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“…As part of the instrument validation, it is important to ensure the uniformity of assessment across different demographic groups. Such a study is known as measurement invariance (MI) (13). Technically, it is important to test whether the probability of responding to a specific item differs across different identifiable groups after controlling for the construct being measured (13).…”

Section: Introductionmentioning

confidence: 99%

A Differential Item Functioning (DIF) Study of the Infection Control Standard Isolation Precaution Instrument Across Gender and Major Among Healthcare Workers

et al. 2021

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Background: Measuring healthcare workers’ (HCWs) knowledge, attitudes, and practices (KAPs) regarding isolation precaution is essential for infection control which needs a valid and reliable instrument. Objectives: This study aimed to assess differential item functioning (DIF) across gender and major for the knowledge and practice items of the questionnaire, previously designed in Shiraz, Iran. Methods: This cross-sectional survey was conducted on 1070 participants (males/females: 306/764; medical students/nurses: 466/624). The study instrument had three subscales with nine questions for each KAP subscale. The Mantel-Haenszel (MH) statistic was used. The DIF and differential test functioning (DTF) analyses were also performed in this study. Results: There were very similar DIF outcomes for the knowledge and practice subscales, with one or two items indicating moderate DIF but comparable total scores across genders. Across majors, several items showed large DIF for both subscales. It was found that large DTF affects major for both subscales. Conclusions: Our findings indicated large DIF and DTF levels of the questionnaire among medical students and nursing groups. More attention should be paid when developing the items. This study shows the importance of paying attention to valid evidence for instruments developed within the field of healthcare.

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“…Measurement nonequivalence can occur at different levels such as instrument or item level resulting in noncomparable data across groups [1–4]. The latter, which is known as differential item functioning (DIF), is an important part of a validation study.…”

Section: Introductionmentioning

confidence: 99%

“…The latter, which is known as differential item functioning (DIF), is an important part of a validation study. DIF analysis which originated in educational testing has been used in psychometric studies to assess whether the probability of responding to a specific item exhibits different statistical properties for different identifiable groups after controlling the construct being measured [1, 4]. There are two forms of DIF known as uniform and nonuniform.…”

Section: Introductionmentioning

confidence: 99%

Assessment of Differential Item Functioning in Health-Related Outcomes: A Simulation and Empirical Analysis with Hierarchical Polytomous Data

Sharafi

Mousavi

Ayatollahi

et al. 2017

Computational and Mathematical Methods in Medicine

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Background The purpose of this study was to evaluate the effectiveness of two methods of detecting differential item functioning (DIF) in the presence of multilevel data and polytomously scored items. The assessment of DIF with multilevel data (e.g., patients nested within hospitals, hospitals nested within districts) from large-scale assessment programs has received considerable attention but very few studies evaluated the effect of hierarchical structure of data on DIF detection for polytomously scored items. Methods The ordinal logistic regression (OLR) and hierarchical ordinal logistic regression (HOLR) were utilized to assess DIF in simulated and real multilevel polytomous data. Six factors (DIF magnitude, grouping variable, intraclass correlation coefficient, number of clusters, number of participants per cluster, and item discrimination parameter) with a fully crossed design were considered in the simulation study. Furthermore, data of Pediatric Quality of Life Inventory™ (PedsQL™) 4.0 collected from 576 healthy school children were analyzed. Results Overall, results indicate that both methods performed equivalently in terms of controlling Type I error and detection power rates. Conclusions The current study showed negligible difference between OLR and HOLR in detecting DIF with polytomously scored items in a hierarchical structure. Implications and considerations while analyzing real data were also discussed.

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Measurement Invariance of Early Development Instrument across age groups

Cited by 3 publications

References 0 publications

Measurement Invariance and Psychometric Analysis of Oxford Happiness Inventory Scale across Gender and Marital Status

Measurement Invariance and Psychometric Analysis of Oxford Happiness Inventory Scale across Gender and Marital Status

A Differential Item Functioning (DIF) Study of the Infection Control Standard Isolation Precaution Instrument Across Gender and Major Among Healthcare Workers

Assessment of Differential Item Functioning in Health-Related Outcomes: A Simulation and Empirical Analysis with Hierarchical Polytomous Data

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